ICRA 2021 论文列表

The recovery of autonomous underwater vehicles (AUVs) has been a challenging mission due to the limited localization accuracy and movement capability of the AUVs. To overcome these limitations, we propose a novel design of a deployable underwater robot (DUR) for the recovery mission. Utilizing the origami structure, the DUR can transform between open and closed states to maximize the performance at different recovery stages. At the approaching stage, the DUR will remain closed state to reduce the drag force. While at the capturing state, the DUR will deploy to form a much larger opening to improve the success rate of docking. Meanwhile, the thrusters’ configuration also changes with the transformation of the robot body. The DUR can achieve a high driven force in the forward direction with the closed state which leads to a fast-approaching speed. While with the open state, the DUR can achieve more balanced force and torque maneuverability to prepare for agile position adjustment for the docking. CFD simulation has been used to analyze the drag forces and identify the hydrodynamic coefficients. A prototype of the robot has been fabricated and tested in an indoor water pool. Both simulation and experiment results validate the feasibility of the proposed design.

This paper proposes a coupled tendon-driven waist joint for humanoid robots. The waist joint was designed as a 3 degrees of freedom (DOF) structure to simulate the motion of a human waist. The power transmission was designed by adopting a 3-motor 3-DOF (3M3D) coupled tendon-driven mechanism, so that the torque on the joints was multiplied. We derived the torque transmission formula and the rotation angle formula of the 3M3D tendon-driven structures and designed the waist joint by adopting an appropriate structure according to their features. To evaluate the accuracy and load capacity of the waist joint, we performed a rotational accuracy experiment and a maximum torque experiment. The experiment results showed that the maximum error of joint rotation was below 1°, and the maximum torque of the pitch, roll, and yaw rotations were 87[Nm], 53[Nm], and 22.2[Nm], respectively.

In spite of recent high attention of the biohybrid robot system, the previous researches focused on actuation system depend on simple on/off control without feedback control. To solve this problem, we proposed a soft sensor for feedback control of a bio-actuator driven by skeletal muscle. The proposed soft sensor can measure contraction forces of the proposed bio-actuator [1]. The bio-actuator was constructed with tendon structure and culture template made by polydimethylsiloxane (PDMS). It generated contraction forces at 0.3 mN when applying electrical stimulation. To measure that kind of small amount of contraction forces (0.3 mN), we fabricated a soft sensor using liquid metal, Galinstan, and HTV-2000. At first, we measured the Young’s modulus of the bioactuator and sensor and then fabricated the soft sensor having 68.52 kPa of Young’s modulus that is similar the bioactuator (45.8 kPa). Next, we simulated the sensor to estimate the resistance change according to the applied force. Since the resistance change is too small, we design the circuit to amplify the signal. Then, we detect very small resistance at milli-ohm. In addition, we analyzed time response to detect signal of actuator faster than 200 ms. As a result, the proposed sensor can measure the force of bioactuator without time delay.

The autonomous robots consisting of an immovable lander and a rover are widely deployed to explore extraterrestrial planets. However, these robots have two main limitations: (1) the separate design for lander and rover respectively results in heavy mass and big volume of the whole system, which increases the launching cost sharply; (2) the rover’s detection area has to be restricted to the vicinity of the immovable lander. To overcome these problems, we designed a novel six-legged mobile repetitive lander called "HexaMRL", which integrates the functions of both lander and rover, including folding, deploying, repetitive soft-landing, and walking. A hybrid compliant mechanism taking advantages of both active and passive compliances was adopted on its leg. An integrated drive unit (IDU) was utilized to imitate the dynamics of a spring and a damper to absorb the landing impact energy, while the structure remains intact. Moreover, a control method based on state machine for soft-landing on the Moon was proposed. HexaMRL achieved repetitive soft-landing on a 5-DoF lunar gravity testing platform (5-DoF-LGTP) with a vertical landing velocity of 1.9 m/s and a payload of 140 kg. The drive torque safety margin is improved by 23.4%p based on the hybrid compliant leg comparing with the standalone active compliant leg.

How best to attach exoskeletons to human limbs is an open and understudied problem. In the case of upperbody exoskeletons, cylindrical handles are commonly used attachments due to ease of use and cost effectiveness. However, handles require active grip strength from the user and may result in undesirable flexion synergy stimulation, thus limiting the robot’s effectiveness. This paper presents a new design, the Eminence Grip, for attaching an exoskeleton to the hand while avoiding the undesirable consequences of using a handle. The ergonomic design uses inverse impedance matching and does not require active effort from the user to remain interfaced with the exoskeleton. We compare the performance of the Eminence Grip to the handle design in a healthy subject target reaching experiment. The results show that the Eminence Grip achieves similar performance to a handle in terms of relative motion between the user and the exoskeleton while eliminating the requirement of grip force to transfer loads to/from the exoskeleton and avoiding stimulation of the flexion synergy. Taken together, the kinematic equivalence and improvement in ergonomics suggest that the Eminence Grip is a promising exoskeleton-hand attachment interface supporting further experiments with impaired populations.

Lightly-damped dynamics of a flexure-based mechanism will tend to largely deteriorate the broadband control performance if its hysteresis nonlinearity has been compensated. This paper developed a novel damped piezo-driven decoupled XYZ nanopositioning stage, which consists of three orthogonal parallel kinematic subchains, in which each subchain has a translational pair using a bridge-type piezo-driven actuator and two Cardan joints using two orthogonal- axis flexure hinges. Especially, we add damped inserts into each Cardan joint, as their shearing damping effects can enhance joint damping. Kinematic coupling is theoretically modeled and the decoupled dynamic model of the stage is built up. The frequency response functions with no-damping and damping scenarios are obtained by finite element transient analysis and experimental modal analysis respectively. The results indicate that the damping inserts embedded in the flexure hinges can enhance the stiffness and damping simultaneously, which will benefit broadband motion control of the nanopositioning stage.

Our goal is to investigate different approaches to modulate stiffness and apply them to human-robot interaction. Here we report on our effort employing the concept of adjustable unsupported-length cantilever leaf spring, which has been previously applied to different designs of variable stiffness actuators. By transmitting the interaction force through the elastic component directly to the supporting structure instead of the actuation unit, this type of actuator requires low power to adjust and to maintain a desired stiffness. In the design of a 1-translational degree of freedom body weight support system of a rehabilitation robot, we used a leaf spring mechanism for stiffness modulation relying only on the spring deflection in combination with a non-backdrivable actuator for adjusting the vertical equilibrium position. This paper describes our approach in determining the spring parameters to attain a desired range of stiffness with a short traveling distance of the adjuster. To model the spring stiffness under deflection, the ideal cantilever support model cannot be assumed for a conventional design of dual roller-pairs slider, especially with a soft spring. A beam deflection model considering the non-zero slopes at the contact points between the rollers and the spring is presented, along with the validation experiments using different spring thicknesses on our prototype.

Crawling through various terrains has been a long research interest. In recent years, quite a number of soft crawling robots have been developed. However, locomoting in an elastic, humid, and slippery environment remains a challenge. In nature, gastropods, such as snails, live in humid environment and could crawl through all kinds of surface conditions by using wet adhesion. In the wet adhesive locomotion, the mucus is crucial in adhering the gastropod while allowing forward motion. Previously, we presented one snail-like soft robot that mimics the gastropods. In this work, we propose a second version and present a theoretical model of the mucus simulant. In addition, the dynamic model of the soft robot’s wet adhesive locomotion is developed for the first time. Results show that the speed of the current version is 5 times than that of the previous one through the optimization of design. Also shown by the results that the mucus helps to speed up the robot by at least 2.7 times.

Driven by the SARS-CoV-2 pandemic, demand for oropharyngeal swab sampling (OP-swabs) is surging. However, medical staff can easily become infected by the virus during the sampling process. In an effort to combat this, we developed a novel, intrinsically safe rigid- flexible coupling (RFC) manipulator to improve the safety and reliability of OP-swab sampling to test for COVID-19, which is presented herein. Suitable sampling areas and the necessary contact force for OP-swab sampling tasks are carefully investigated, and three typical sampling paths outlined that could be performed by a robotic system. This is followed by a detailed description of an intrinsically safe bionic micro-pneumatic actuator (MPA) that was designed and fabricated as the main component of the RFC manipulator. The developed RFC manipulator’s kinematic modeling, motion planning, and force control capacities were designed for OP-swab sampling scenarios. The system was then validated using both an oral cavity phantom and human volunteers, with comparative experiments on the swab quality of the OP-swab sampling approach conducted in both robotic and manual modes. The results indicate that fully-automated sampling based on this design would be feasible.

The reactor power and the coolant level in the nuclear plant are monitored via the reactor core detectors. Every 4 to 5 years, the detectors with high-level radiation need to be removed, which is time-consuming and hazardous for workers. To address this issue, this paper introduces a novel robotic system and its strategy for the removal of the detectors. The modular mechanisms are designed to achieve diverse actions such as positioning, extracting, transporting, cutting, and coiling. The detector with different radiation doses is physically classified and minimized in volume. The experiments to simulate the removal process are conducted. The results demonstrate that the time for the robotic removal of one detector is reduced from more than 1 hour to 31.2±5.3 min compared with the manual mode. The radiation exposure time for workers is reduced to 0 under normal working conditions, which significantly reduces the radiation dose compared with the traditional methods.

This paper designed a pneumatic soft climbing robot by utilizing the high flexibility of soft materials. Capabilities of climbing and creeping through small spaces would rarely possible with a method based only on rigid links. At first, according to the drive mode of pneumatic networks, a model for soft climbing robots with different section having their independent stiffness was designed; afterwards, the analysis of visco-mechanical properties of robots at the contact surface were provided by using the method of minimum potential energy; on the basis, finite element analysis and experiment are given to analyze the climbing behaviors of the robot; finally, by employing 3-d printing and layer-by-layer casting, a prototype soft climbing robot was prepared to perform climbing experiments. The research is expected to provide a new method for monitoring complex unstructured environments.

In this study, a novel robotic bioreactor is presented with capabilities of closed-loop control of force and displacement applied to a tissue scaffold and tissue scaffold stiffness calculation. These characteristics bring the potential of a robotic bioreactor that can optimize the mechanical properties of tissue constructs in order for them to match those of native tissues. Custom position and force control signals are designed to maintain a steady tensioning of the tissue scaffold while the latter one’s mechanical properties evolve in time. We propose a simple model to support the hypothesis that the stiffness of a cell-seeded scaffold increases over time, and thus force control signals need to be adjusted accordingly. The robotic bioreactor is able to measure the stiffness of a scaffold sample relatively accurately, with an average standard deviation of 0.2N/mm. The combination of accurate stiffness measurements and a closed-loop control system equips the robotic bioreactor with the fundamental requirements to achieve stiffness based force control in future in vitro experiments, and thus to a tissue-scaffold responsive technology for advanced tissue engineering.

This paper presents the design and control of a fully handheld robot for robot-assisted microsurgery. The handheld robot incorporates a miniature 6-PUS parallel micromanipulator that can impose a remote center of motion (RCM) at the incision point of entry during microsurgery. An optimization framework is formulated to determine the geometric parameters of the micromanipulator. The optimization aims to minimize force applied on actuation modules by lateral load at the RCM. The optimization yields a base diameter of 16 mm, a top diameter of 12.6 mm, and a connecting link of 9.4 mm, which offers a cylindrical workspace 4-mm wide and 3-mm high with a 5-mm travel in linear actuation. An order of magnitude higher force capability is attained in the smaller form factor compared to the latest handheld micromanipulator. We built the fully handheld version of the microsurgical robot by incorporating embedded electronics and an EM tracker for sensing the 6-DOF pose of hand motion. The real-time control framework of the handheld robot is also presented, including motion filter for active tremor cancellation. As a result, the handheld robot can tolerate side loads up to 5.0 N for a lateral load applied at the RCM without significant degradation in control. Finally, the robot-aided operation with the active tremor cancellation shows a significant peak-force reduction compared to unaided operation during the task of maintaining contact force.

This paper presents the mechanism and design of a robotically steerable catheter system for percutaneous and minimally invasive treatment of mitral regurgitation. One of the main causes of mitral regurgitation is an impaired mitral valve topology, that results in severe heart-related diseases. Repair or replacement of the mitral valve through open-heart surgery such as traditional sternotomy has been conducted as a treatment. However, at least 50 % of patients with severe mitral regurgitation are not candidates for this surgery due to their age or comorbidities. Recently, minimally invasive or transcatheter approaches for mitral valve repair/replacement have been gaining attention to minimize the surgery's risk and several catheter mechanisms have been proposed in early phase clinical trials. Although dexterity and manipulability are essential functions in the transcatheter procedure, a direct torsional capability has not been implemented in the systems. We present a design of a 5-DoF robotically steerable catheter having two bending joints, two torsion joints having a direct torquing design, and a mitral implant delivery module to provide dexterous manipulation of the tip of the catheter. Designs and kinematic models of each joint module are presented and their performance is verified with experiments. Lastly, a mitral clip implanting procedure is demonstrated in a phantom heart model.

Soft robots are compliant to wrap large objects and adaptive to unstructured environments, while rigid robots can bend discretely at joints and pinch small objects easily. In this paper, we aim to create a novel robot that can behave like a rigid or soft robot adaptively, without additional stiffness-tunable mechanism. This approach makes the robot lightweight and practical. First, we present the fabricating process of the soft-rigid robot developed in the work. A steel flexure is especially optimized and embedded in the flexible body of the robot, which enhances the bending stiffness in the axial direction dramatically while keeping the body in other directions flexible and adaptive. Second, the kinematic model and analysis are developed to characterize the different configurations of the soft-rigid robot influenced by various parameters. Third, experiments are conducted to evaluate the performance of the flexible body and validate the accuracy of the kinematic model. Finally, a two-fingered gripper is built based on the soft-rigid robots, and grasping experiments are conducted to demonstrate how the soft-rigid robots could enhance the capability of the gripper in real-word.

In this paper, we focus on a rarely used paradigm in the design of underactuated robot hands: the use of springs as agonists and tendons as antagonists. We formalize this approach in a design matrix also considering its interplay with the underactuation method used (one tendon for multiple joints vs. multiple tendons on one motor shaft). We then show how different cells in this design matrix can be combined in order to facilitate the implementation of desired postural synergies with a single motor. Furthermore, we show that when agonist and antagonist tendons are combined on the same motor shaft, the resulting spring force cancellation can be leveraged to produce multiple desirable behaviors, which we demonstrate in a physical prototype.

Steerable needles that are able to follow curvilinear trajectories and steer around anatomical obstacles are a promising solution for many interventional procedures. In the lung, these needles can be deployed from the tip of a conventional bronchoscope to reach lung lesions for diagnosis. The reach of such a device depends on several design parameters including the bronchoscope diameter, the angle of the piercing device relative to the medial axis of the airway, and the needle’s minimum radius of curvature while steering. Assessing the effect of these parameters on the overall system’s clinical utility is important in informing future design choices and understanding the capabilities and limitations of the system. In this paper, we analyze the effect of various settings for these three robot parameters on the percentage of the lung that the robot can reach. We combine Monte Carlo random sampling of piercing configurations with a Rapidly-exploring Random Trees based steerable needle motion planner in simulated human lung environments to asymptotically accurately estimate the volume of sites in the lung reachable by the robot. We highlight the importance of each parameter on the overall system’s reachable workspace in an effort to motivate future device innovation and highlight design trade-offs.

We propose a framework for deformable linear object prediction. Prediction of deformable objects (e.g., rope) is challenging due to their non-linear dynamics and infinite-dimensional configuration spaces. By mapping the dynamics from a non-linear space to a linear space, we can use the good properties of linear dynamics for easier learning and more efficient prediction. We learn a locally linear, action-conditioned dynamics model that can be used to predict future latent states. Then, we decode the predicted latent state into the predicted state. We also apply a sampling-based optimization algorithm to select the optimal control action. We empirically demonstrate that our approach can predict the rope state accurately up to ten steps into the future and that our algorithm can find the optimal action given an initial state and a goal state.

Bipedal walking is one of the most difficult but exciting challenges in robotics. The difficulties arise from the complexity of high-dimensional dynamics, sensing and actuation limitations combined with real-time and computational constraints. Deep Reinforcement Learning (DRL) holds the promise to address these issues by fully exploiting the robot dynamics with minimal craftsmanship. In this paper, we propose a novel DRL approach that enables an agent to learn omnidirectional locomotion for humanoid (bipedal) robots. Notably, the locomotion behaviors are accomplished by a single control policy (a single neural network). We achieve this by introducing a new curriculum learning method that gradually increases the task difficulty by scheduling target velocities. In addition, our method does not require reference motions which facilities its application to robots with different kinematics, and reduces the overall complexity. Finally, different strategies for sim-to-real transfer are presented which allow us to transfer the learned policy to a real humanoid robot.